Weis Markets (WMK) Total Liabilities (2010 - 2026)
Weis Markets (WMK) recorded Total Liabilities of $658.18 million in Q2 2026, up 5.4% from $624.25 million a year earlier and up 0.3% from the prior quarter.
Weis Markets (WMK) Total Liabilities (2010 - 2026) Analysis & Trends
At the end of FY2025, Weis Markets reported Total Liabilities of $675.45 million, up 2.8% from FY2024.
- Annual Total Liabilities has a five-year compound annual growth rate of 0.0% (FY2020 to FY2025).
- Across earlier years, Total Liabilities came in at $656.95 million in FY2024 (-0.8%), $662.24 million in FY2023 (+1.1%), $655.34 million in FY2022 (-5.1%) and $690.73 million in FY2021 (+2.4%).
- Quarterly Total Liabilities has ranged from $576.5 million in Q3 2023 to $690.73 million in Q4 2021 over the past five years.
- On a year-over-year basis, Total Liabilities has increased for four consecutive quarters, with growth averaging 2.7% over the last eight quarters.
- Peak year-over-year performance for Total Liabilities in the last five years was growth of 12.4% in Q3 2024, against a decline of 12.6% in Q3 2023 at the low end.
- Per Business Quant, the preceding three quarters came in at $656.28 million (Q1 2026), $675.45 million (Q4 2025) and $669.92 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Walmart | 950.11 Bn | 906.54 Bn | 49.13 Bn | 189.41 Bn |
| 2 | Costco Wholesale | 443.29 Bn | 366.57 Bn | 12.19 Bn | 53.24 Bn |
| 3 | Sysco | 39.29 Bn | 33.53 Bn | 4.13 Bn | 25.73 Bn |
| 4 | Kroger | 38.91 Bn | 25.07 Bn | 7.86 Bn | 43.65 Bn |
| 5 | Dollar General | 29.77 Bn | 24.45 Bn | 3.68 Bn | 22.88 Bn |
| 6 | Caseys General Stores | 26.14 Bn | 24.13 Bn | 1.24 Bn | 5.03 Bn |
| 7 | Dollar Tree | 24.02 Bn | 20.64 Bn | 2.10 Bn | 10.60 Bn |
| 8 | US Foods Holding | 22.11 Bn | 21.91 Bn | 1.92 Bn | 10.06 Bn |
| 9 | Tractor Supply | 17.23 Bn | 16.40 Bn | 1.68 Bn | 9.53 Bn |
| 10 | Weis Markets | 1.86 Bn | 1.06 Bn | 328.40 Mn | 658.18 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 27, 2026 | 658.18 Mn |
| Mar 28, 2026 | 656.28 Mn |
| Dec 27, 2025 | 675.45 Mn |
| Sep 27, 2025 | 669.92 Mn |
| Jun 28, 2025 | 624.25 Mn |
| Mar 29, 2025 | 619.58 Mn |
| Dec 28, 2024 | 656.95 Mn |
| Sep 28, 2024 | 647.91 Mn |
| Jun 29, 2024 | 649.36 Mn |
| Mar 30, 2024 | 644.94 Mn |
| Dec 30, 2023 | 662.24 Mn |
| Sep 30, 2023 | 576.50 Mn |
| Jul 1, 2023 | 628.31 Mn |
| Apr 1, 2023 | 624.49 Mn |
| Dec 31, 2022 | 655.34 Mn |
| Sep 24, 2022 | 659.64 Mn |
| Jun 25, 2022 | 663.34 Mn |
| Mar 26, 2022 | 659.46 Mn |
| Dec 25, 2021 | 690.73 Mn |
| Sep 25, 2021 | 665.46 Mn |
Weis Markets Total Liabilities API
Pull this series into your own models, spreadsheets and apps with the Business Quant
Historical Metrics API. The request below matches the chart above — change the
frequency, period or values and it follows. Swap YOUR_API_KEY for your own key.
https://data.businessquant.com/historic?slug=total-liabilities&ticker=WMK&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-liabilities", "ticker": "WMK", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=total-liabilities&ticker=WMK&period=max&api_key=YOUR_API_KEY");
const data = await res.json();